GA-TNG | Geometric algorithms for transport network graphs

Summary
Graphs have been used to analyse transport networks for hundreds of years. However, graphs are general structures and many graph algorithms are very slow. Specialised algorithms are much more efficient but can only be applied to restricted graph classes. Transport network graphs suffer from a lack of efficient specialised algorithms, since most graph classes are too restrictive and do not accurately represent real-world transport networks.

Recent developments have led to geometric graph classes that are tailored to real-world transport networks. One of these geometric graph classes, phi-low-density graphs, captures the property that there are more connections between geographically nearby nodes than geographically distant ones. Unfortunately, the fundamental properties of phi-low-density graphs are not well understood, which has prevented the development of a wide range of specialised algorithms.

My objective is to fill the acute need for a simple and versatile graph class that accurately represents real-world transport networks. My research will allow experts to finally harness the power of specialised algorithms on a wide range of important transport network problems. I will achieve my objectives through two sub-objectives: (1) To build fundamental structures for phi-low-density graphs, and (2) To design provably efficient specialised algorithms for phi-low-density graphs.

I will be support by my host institution (University of Copenhagen), my host group (Basic Algorithms Research Copenhagen), my primary supervisor (Mikkel Abrahamsen), and my secondary supervisor (Rasmus Pagh).
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101146276
Start date: 01-03-2025
End date: 28-02-2027
Total budget - Public funding: - 230 774,00 Euro
Cordis data

Original description

Graphs have been used to analyse transport networks for hundreds of years. However, graphs are general structures and many graph algorithms are very slow. Specialised algorithms are much more efficient but can only be applied to restricted graph classes. Transport network graphs suffer from a lack of efficient specialised algorithms, since most graph classes are too restrictive and do not accurately represent real-world transport networks.

Recent developments have led to geometric graph classes that are tailored to real-world transport networks. One of these geometric graph classes, phi-low-density graphs, captures the property that there are more connections between geographically nearby nodes than geographically distant ones. Unfortunately, the fundamental properties of phi-low-density graphs are not well understood, which has prevented the development of a wide range of specialised algorithms.

My objective is to fill the acute need for a simple and versatile graph class that accurately represents real-world transport networks. My research will allow experts to finally harness the power of specialised algorithms on a wide range of important transport network problems. I will achieve my objectives through two sub-objectives: (1) To build fundamental structures for phi-low-density graphs, and (2) To design provably efficient specialised algorithms for phi-low-density graphs.

I will be support by my host institution (University of Copenhagen), my host group (Basic Algorithms Research Copenhagen), my primary supervisor (Mikkel Abrahamsen), and my secondary supervisor (Rasmus Pagh).

Status

SIGNED

Call topic

HORIZON-MSCA-2023-PF-01-01

Update Date

03-10-2024
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Horizon Europe
HORIZON.1 Excellent Science
HORIZON.1.2 Marie Skłodowska-Curie Actions (MSCA)
HORIZON.1.2.0 Cross-cutting call topics
HORIZON-MSCA-2023-PF-01
HORIZON-MSCA-2023-PF-01-01 MSCA Postdoctoral Fellowships 2023